Teaching in 2013Machine Learning Tutorial, KAIST  MLT 2013Distances and Kernels in Machine LearningA simple Matlab GUI to illustrate metric learning with ITML or LMNN and 3 labels. Foundations of Intelligent Systems, Kyoto U. (Spring 2013)Part I, Statistical Machine LearningApril 16th  May 28th
Recommended reading for derivatives and gradients: Appendix A.4 of this book Homework 1, due May 7th (Tue) noon, either in paper form in the course mailbox or sent to this this email. Homework 2, due May 21st (Tue) noon. Please send your homework to this email. Homework 3, due July 9th (Tue) noon. Please send your homework to this email. Teaching Assistant: Tam Le Pattern Recognition Advanced, Kyoto U. (Spring 2013)SVM, CRF’s and Topic ModelsJuly 3  July 17
Introduction to Information Sciences, Kyoto U. (Fall 2013)Here are the slides
Large Scale Optimization and Machine Learning, Kyoto U. (Fall 2013)Recommended reading to take the course
